A public security intelligent police dispatching method, system and device based on linkage of a vehicle-mounted terminal

Abstract

This invention discloses a method, system, and device for intelligent police dispatching based on vehicle-mounted terminal linkage, relating to the fields of public security informatization and intelligent dispatching technology. The method mainly includes: selecting candidate vehicle-mounted terminals from multiple terminals based on event location information; determining the target vehicle-mounted terminal by matching and scoring police resources based on alarm information and the status information of each candidate terminal; receiving and presenting dispatch instructions; obtaining alarm feedback operations and generating officer operation results; continuously reporting location information using the target vehicle-mounted terminal when the officer accepts the task; collecting on-site video data using the target vehicle-mounted terminal after it arrives at the event location; and performing dynamic dispatching based on the aforementioned information. Implementing the intelligent police dispatching method, system, and device based on vehicle-mounted terminal linkage provided by this invention can improve the response efficiency, accuracy, and dispatching flexibility of police dispatching in complex police scenarios.

Description

Technical Field

[0001] This invention relates to the field of public security informatization and intelligent dispatching technology, and more specifically, to a public security intelligent dispatching method, system and device based on vehicle-mounted terminal linkage. Background Technology

[0002] Currently, police dispatch mainly relies on the 110 emergency call system, where dispatchers manually assess the alarm information and select officers based on experience. While this method can accomplish basic dispatch tasks in general emergency situations, it still has many limitations in complex situations, emergencies, and scenarios with multiple interfering factors.

[0003] On the one hand, current police dispatch decisions typically rely on human experience and lack a unified quantitative evaluation mechanism, making it difficult to objectively and stably screen and compare candidate police forces. This can easily lead to unreasonable allocation of police resources and low response efficiency. On the other hand, existing technologies usually only screen police forces based on distance, jurisdiction, or simple location information, without fully considering factors such as estimated arrival time, geographical environment, weather conditions, social environment, and the current status of vehicle terminals. This makes it difficult to meet the requirements for accuracy and real-time dispatch in complex police scenarios.

[0004] Furthermore, in existing police dispatch systems, vehicle-mounted terminals typically function merely as passive recipients of dispatch instructions, lacking deep involvement in feedback and decision-making during dispatch execution and lacking a real-time linkage mechanism with the dispatch system. Especially during actual dispatch operations, situations may arise where target officers refuse to cooperate, fail to arrive on time, deviate from their course en route, or experience escalating risks. Existing technologies struggle to dynamically reschedule these officers by combining location information from the vehicle-mounted terminals, officer feedback, and on-site video data, thus failing to establish a closed-loop response process of "dispatch—execution—feedback—rescheduling."

[0005] Therefore, it is necessary to propose a public security intelligent dispatching technology solution that can comprehensively screen candidate police forces based on multi-dimensional environmental factors and dynamically dispatch them by combining information from vehicle-mounted terminals and on-site video data, so as to improve the dispatching efficiency, dispatching accuracy and police resource utilization efficiency in complex police scenarios. Summary of the Invention

[0006] The purpose of this invention is to provide a method, system, and device for intelligent police dispatch based on vehicle-mounted terminal linkage, which can improve the response efficiency, accuracy, and scheduling flexibility of police dispatch in complex police scenarios.

[0007] This invention provides a method for intelligent police dispatching based on vehicle-mounted terminal linkage, comprising the following steps: S1: Receive alarm information sent by the alarm system, wherein the alarm information includes at least event location information and case description information; S2: Based on the event location information, select candidate vehicle terminals from multiple vehicle terminals and obtain the status information of each candidate vehicle terminal; S3: Based on the alarm information and the status information of each candidate vehicle terminal, a police force matching score is performed on each candidate vehicle terminal, and the target vehicle terminal is determined based on the police force matching score. S4: Utilize the target vehicle terminal to receive and present the dispatch command, obtain the alarm feedback operation, and generate the police officer's operation result; S5: Confirm that the police officer's operation result is that the police officer accepts the task, continuously report the location information using the target vehicle terminal, confirm that the target vehicle terminal has arrived at the event location, and collect on-site video data using the target vehicle terminal; S6: Dynamic scheduling is performed based on the police officer's operation results, location information, and on-site video data to dispatch additional, replace, or coordinate dispatch of police officers.

[0008] Furthermore, the step of selecting candidate vehicle terminals from multiple vehicle terminals based on the event location information includes: obtaining the spatial distance between each vehicle terminal and the event location, estimated arrival time, geographical environment information, weather environment information, social environment information, and the current status information of the vehicle terminal; calculating the candidate screening value corresponding to each vehicle terminal based on the spatial distance, estimated arrival time, geographical environment information, weather environment information, social environment information, and the current status information of the vehicle terminal; and determining the vehicle terminals whose candidate screening values ​​meet the preset screening conditions as candidate vehicle terminals.

[0009] Furthermore, the formula for calculating the candidate screening value is as follows: F = a1·D + a2·T + a3·G + a4·W + a5·Q Where F is the candidate screening value, D is the distance factor, T is the estimated arrival time factor, G is the geographical accessibility factor, W is the weather impact factor, Q is the terminal availability factor, and a1, a2, a3, a4 and a5 are the corresponding weight coefficients.

[0010] Further, step S3 specifically includes: calculating the police force matching score of each candidate vehicle terminal based on the status information of each candidate vehicle terminal; sorting the candidate vehicle terminals according to their police force matching scores, and selecting the candidate vehicle terminal with the highest police force matching score as the target vehicle terminal.

[0011] Furthermore, the formula for calculating the police force matching score is as follows: S = b1·R + b2·E + b3·U + b4·M + b5·C Where S is the police force matching score, R is the expected response efficiency factor, E is the police officer's historical handling efficiency factor, U is the current task load factor, M is the incident type matching factor, C is the communication and video capability factor, and b1, b2, b3, b4 and b5 are the corresponding weight coefficients.

[0012] Furthermore, the dynamic scheduling process includes: The location information continuously reported by the target vehicle terminal is analyzed to obtain a location analysis result. The location analysis result includes location anomalies, which include failure to arrive within time limit, deviation from the preset route, and long-term stagnation. Keyframe extraction and risk identification are performed on the on-site video data to obtain video risk identification results, which include crowd gathering, conflict escalation, traffic congestion, and pre-set dangerous behaviors. Based on the location anomaly, video risk identification results, police officer feedback on the degree of anomaly, and historical police incident correlation information, a dynamic dispatch trigger value is calculated; when the dynamic dispatch trigger value is higher than a preset threshold, steps S2 and S3 are executed.

[0013] Furthermore, the formula for calculating the dynamic scheduling trigger value is as follows: P = c1·L + c2·V + c3·A + c4·H Where P is the dynamic scheduling trigger value, L is the location anomaly factor, V is the video risk identification factor, A is the police officer feedback anomaly factor, H is the historical police incident correlation factor, and c1, c2, c3 and c4 are the corresponding weight coefficients.

[0014] This invention also provides a public security intelligent dispatching system based on vehicle-mounted terminal linkage, comprising: An alarm information receiving module is used to receive alarm information sent by an alarm system. The alarm information includes at least event location information and case description information. The candidate terminal filtering module is used to filter candidate vehicle terminals from multiple vehicle terminals based on the event location information, and to obtain the status information of each candidate vehicle terminal. The scoring calculation module is used to perform police force matching scoring on each candidate vehicle terminal based on the alarm information and the status information of each candidate vehicle terminal, and to determine the target vehicle terminal based on the police force matching score. The dispatch instruction module is used to receive and present dispatch instructions using the target vehicle terminal, obtain alarm feedback operations, and generate police officer operation results. The terminal feedback processing module is used to confirm that the police officer's operation result is that the police officer has accepted the task, continuously report location information using the target vehicle terminal, confirm that the target vehicle terminal has arrived at the event location, and collect on-site video data using the target vehicle terminal; The dynamic scheduling module is used to dynamically schedule officers based on their operational results, location information, and on-site video data, and to dispatch additional officers, replace dispatched officers, or coordinate dispatch of officers.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described intelligent police dispatch method based on vehicle terminal linkage.

[0016] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described intelligent police dispatch method based on vehicle terminal linkage.

[0017] The intelligent police dispatching method, system, and device based on vehicle-mounted terminal linkage provided by this invention have the following beneficial effects: This invention addresses the problems in existing technologies, such as reliance on human experience in dispatching police officers, limited dimensions in candidate officer selection, insufficient utilization of vehicle-mounted terminal feedback, and difficulty in dynamically rescheduling officers based on changes in the scene. In the candidate vehicle-mounted terminal selection stage, this invention no longer relies solely on spatial distance for simple selection, but comprehensively considers estimated arrival time, geographical environment, weather environment, social environment, and terminal status information. This enables more accurate identification of candidate police officers suitable for participating in the current police situation, improving the rationality and effectiveness of candidate terminal selection.

[0018] This invention constructs a police force matching scoring mechanism to comprehensively and quantitatively evaluate the expected response efficiency, historical handling efficiency, current task load, matching degree of police incident type, and communication and video capabilities of candidate vehicle terminals. This reduces the reliance on human experience in the dispatching process and improves the scientificity and consistency of target police force selection.

[0019] This invention enables bidirectional interaction between the vehicle-mounted terminal and the police dispatch system, allowing the vehicle-mounted terminal to not only receive dispatch instructions but also provide feedback on the police officer's call results, dispatch location status, and on-site video information. This achieves a closed-loop linkage between dispatch, execution, and feedback, improving the controllability and traceability of the dispatch process.

[0020] This invention combines police officer feedback, location anomaly information, and on-site video data to identify abnormal situations and on-site risks during task execution. When preset scheduling conditions are met, a dynamic rescheduling process is triggered to increase police force, replace execution terminals, or coordinate police dispatch, thereby improving real-time response capabilities and scheduling flexibility in complex police scenarios.

[0021] This invention collects and transmits on-site video data through a vehicle-mounted terminal, enabling the police dispatch system to conduct risk analysis and auxiliary judgment based on changes in the on-site situation. This provides the command center with more timely and realistic on-site information support, thereby improving the accuracy of the judgment and decision-making efficiency of the police situation handling plan.

[0022] This invention achieves refined allocation of police resources by combining multi-factor screening, scoring decision-making, and dynamic scheduling. It avoids problems such as misallocation of police force, duplicate dispatch, or scheduling delays caused by relying solely on distance or human experience, thereby improving the overall resource utilization efficiency and coordination capabilities of the public security dispatch system.

[0023] This invention further introduces a hierarchical adaptive dispatch decision algorithm. By normalizing each factor in the candidate screening value, police force matching score value and dynamic scheduling trigger value, and combining the alarm type, regional environmental characteristics, historical handling data and real-time feedback information to dynamically correct the weights, the dispatch model's adaptability to different alarm types, complex regional environments and changes in the on-site situation is enhanced. This is conducive to improving the stability, robustness and practicality of dispatch decisions in complex scenarios.

[0024] In summary, this invention receives alarm information from an alarm system; selects candidate vehicle terminals from multiple vehicle terminals based on event location information and obtains the status information of each candidate vehicle terminal; performs police force matching scoring on each candidate vehicle terminal based on the alarm information and the status information of the candidate vehicle terminals, and determines the target vehicle terminal based on the scoring results; sends a dispatch command to the target vehicle terminal, and the vehicle terminal receives the police officer's alarm response; when the police officer accepts the task, he continuously reports his location information through the vehicle terminal during the dispatch process, and collects and transmits on-site video data after arriving at the scene; performs dynamic scheduling based on the police officer's operation results, location information, and on-site video data, and re-executes the candidate vehicle terminal selection and police force matching scoring when preset scheduling conditions are met, so as to dispatch additional, replace, or coordinate police dispatch. This invention constructs a multi-factor candidate terminal screening mechanism, a police force matching and scoring mechanism, and a dynamic scheduling mechanism based on feedback information and video data. It also normalizes each factor and adaptively adjusts its weights, thereby realizing the intelligent, closed-loop, and dynamic dispatching process. This improves the dispatching efficiency and handling accuracy in complex police scenarios, as well as the response efficiency, dispatching accuracy, and scheduling flexibility in complex police scenarios. Attached Figure Description

[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart of the intelligent police dispatching method based on vehicle terminal linkage provided by the present invention; Figure 2This is a schematic diagram of the structure of the intelligent police dispatch system based on vehicle terminal linkage provided by the present invention; Figure 3 This is a flowchart illustrating the intelligent police dispatching method based on vehicle-mounted terminal linkage provided by the present invention. Figure 4 This is a schematic diagram of the police intelligent dispatching sequence based on vehicle terminal linkage provided by the present invention; Figure 5 This is a comparison and verification result diagram provided by the present invention; Figure 6 This is a structural block diagram of the electronic device provided by the present invention. Detailed Implementation

[0026] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0027] Figure 1 A schematic diagram of the intelligent police dispatching method based on vehicle-mounted terminal linkage according to this embodiment is shown. In this embodiment, the intelligent police dispatching method based on vehicle-mounted terminal linkage includes the following steps: S1: Receive alarm information sent by the alarm system, wherein the alarm information includes at least event location information and case description information; S2: Based on the event location information, select candidate vehicle terminals from multiple vehicle terminals and obtain the status information of each candidate vehicle terminal; In one exemplary embodiment, the selection of candidate vehicle terminals is based not only on the spatial distance between the vehicle terminal and the event location, but also comprehensively considers the estimated arrival time, geographical environment information, weather environment information, social environment information and the current status information of the vehicle terminal, so as to generate candidate selection results. In one exemplary embodiment, the candidate vehicle terminal screening process employs a multi-factor candidate screening model to pre-screen multiple vehicle terminals.

[0028] In one exemplary embodiment, the step of selecting candidate vehicle terminals from multiple vehicle terminals based on the event location information includes: obtaining the spatial distance between each vehicle terminal and the event location, estimated arrival time, geographical environment information, weather environment information, social environment information, and the current status information of the vehicle terminal; calculating the candidate screening value corresponding to each vehicle terminal based on the spatial distance, estimated arrival time, geographical environment information, weather environment information, social environment information, and the current status information of the vehicle terminal; and determining the vehicle terminals whose candidate screening values ​​meet the preset screening conditions as candidate vehicle terminals.

[0029] As an exemplary embodiment, the preset screening condition is as follows: the candidate screening value F is compared with the preset screening threshold F0. When F≥F0, the corresponding vehicle terminal is determined to be qualified to participate in the current emergency response and is included in the candidate terminal set; when F<F0, the corresponding vehicle terminal is determined not to be qualified to participate in the current emergency response.

[0030] In one specific embodiment, the preset screening threshold F0 is set to 0.60.

[0031] In one exemplary embodiment, the formula for calculating the candidate screening value is: F = a1·D + a2·T + a3·G + a4·W + a5·Q Where F is the candidate screening value, D is the distance factor, T is the estimated arrival time factor, G is the geographical accessibility factor, W is the weather impact factor, Q is the terminal availability factor, and a1, a2, a3, a4 and a5 are the corresponding weight coefficients.

[0032] In one exemplary embodiment, the status information of each candidate vehicle terminal includes: the expected response efficiency of each candidate vehicle terminal, the historical handling efficiency of police officers, the current task load, the matching degree of the police situation type, and the terminal communication and video capabilities. S3: Based on the alarm information and the status information of each candidate vehicle terminal, a police force matching score is performed on each candidate vehicle terminal, and the target vehicle terminal is determined based on the police force matching score. In one exemplary embodiment, the police force matching score comprehensively considers the expected response efficiency, the historical handling efficiency of police officers, the current task load, the matching degree of the police situation type, and the terminal communication and video capabilities, so as to improve the accuracy of the selection of the target vehicle terminal. In one exemplary embodiment, the police force matching and scoring process employs a multi-dimensional police force scoring model to sort candidate vehicle terminals and select the target vehicle terminal with the best score.

[0033] In one exemplary embodiment, step S3 specifically includes: calculating the police force matching score of each candidate vehicle terminal based on the status information of each candidate vehicle terminal; sorting the candidate vehicle terminals according to their police force matching scores, and selecting the candidate vehicle terminal with the highest police force matching score as the target vehicle terminal.

[0034] In one exemplary embodiment, step S3 specifically includes: obtaining the expected response efficiency, historical police officer handling efficiency, current task load, crime type matching degree, and terminal communication and video capabilities of each candidate vehicle-mounted terminal; calculating the police force matching score of each candidate vehicle-mounted terminal based on the expected response efficiency, historical police officer handling efficiency, current task load, crime type matching degree, and terminal communication and video capabilities; and determining the candidate vehicle-mounted terminal with the highest score as the target vehicle-mounted terminal based on the ranking result of the police force matching scores of each candidate vehicle-mounted terminal.

[0035] In one exemplary embodiment, the formula for calculating the police force matching score is: S = b1·R + b2·E + b3·U + b4·M + b5·C Where S is the police force matching score, R is the expected response efficiency factor, E is the police officer's historical handling efficiency factor, U is the current task load factor, M is the incident type matching factor, C is the communication and video capability factor, and b1, b2, b3, b4 and b5 are the corresponding weight coefficients.

[0036] S4: Utilize the target vehicle terminal to receive and present the dispatch command, obtain the alarm feedback operation, and generate the police officer's operation result; S5: Confirm that the police officer's operation result is that the police officer accepts the task, continuously report the location information using the target vehicle terminal, confirm that the target vehicle terminal has arrived at the event location, and collect on-site video data using the target vehicle terminal; S6: Dynamically dispatch officers based on their operational results, location information, and on-site video data to increase, replace, or coordinate the dispatch of officers. In one exemplary embodiment, the dynamic scheduling process includes: The location information continuously reported by the target vehicle terminal is analyzed to obtain a location analysis result. The location analysis result includes location anomalies, which include failure to arrive within time limit, deviation from the preset route, and long-term stagnation. Keyframe extraction and risk identification are performed on the on-site video data to obtain video risk identification results, which include crowd gathering, conflict escalation, traffic congestion, and pre-set dangerous behaviors. Based on the location anomaly, video risk identification results, police officer feedback on the degree of anomaly, and historical police incident correlation information, a dynamic dispatch trigger value is calculated; when the dynamic dispatch trigger value is higher than a preset threshold, steps S2 and S3 are executed.

[0037] In one exemplary embodiment, the formula for calculating the dynamic scheduling trigger value is: P = c1·L + c2·V + c3·A + c4·H Where P is the dynamic scheduling trigger value, L is the location anomaly factor, V is the video risk identification factor, A is the police officer feedback anomaly factor, H is the historical police incident correlation factor, and c1, c2, c3 and c4 are the corresponding weight coefficients.

[0038] As an exemplary embodiment, the preset threshold is a dynamic scheduling trigger threshold P0. The dispatch system compares the calculated dynamic scheduling trigger value P with the dynamic scheduling trigger threshold P0. When P > P0, it determines that the current task has a risk of needing to be rescheduled and triggers the dynamic scheduling process; when P ≤ P0, it determines that the current task can still be executed by the existing target vehicle terminal.

[0039] In one exemplary embodiment, the dynamic scheduling trigger threshold P0 is set to 0.65.

[0040] As an exemplary embodiment, step S6 includes: dynamically scheduling based on the police officer's operation results, location information, and on-site video data; and re-executing candidate vehicle terminal screening and police force matching scoring when preset scheduling conditions are met, for the purpose of increasing, replacing, or coordinating police dispatch.

[0041] In one exemplary embodiment, the dynamic scheduling process combines location anomaly analysis, police officer feedback anomaly analysis, video risk identification, and historical police incident correlation analysis to determine whether to trigger a rescheduling process.

[0042] In one exemplary embodiment, the dynamic scheduling based on the police officer's operation result, location information, and on-site video data includes: The location information continuously reported by the target vehicle terminal is analyzed to determine whether there are any abnormal situations such as failure to arrive within the time limit, deviation from the preset route, or long-term stagnation. Keyframe extraction and risk identification are performed on the on-site video data to determine whether there is a gathering of people, escalation of conflict, traffic congestion, or pre-planned dangerous behavior on-site. By combining abnormal information reported by police officers with historical police incident information, it is determined whether dynamic dispatch should be triggered.

[0043] In one exemplary embodiment, determining whether to trigger dynamic scheduling includes: calculating a dynamic scheduling trigger value based on the degree of location anomaly, video risk identification results, the degree of anomaly reported by police officers, and the correlation with historical incidents; and triggering the dynamic scheduling process when the dynamic scheduling trigger value is higher than a preset threshold.

[0044] In one exemplary embodiment, all factors involved in the calculation of the candidate screening value, police force matching score value, and dynamic dispatch trigger value are normalized to eliminate the influence of different dimensions on the comprehensive calculation results and improve the comparability and stability of multi-source heterogeneous data when participating in police dispatch decisions.

[0045] In one exemplary embodiment, the weighting coefficients can be adaptively adjusted based on the type of incident, regional environmental characteristics, historical handling data, and real-time feedback information to improve the accuracy of candidate terminal screening, target terminal selection, and dynamic scheduling determination under different incident scenarios.

[0046] This embodiment provides a public security intelligent dispatching system based on vehicle-mounted terminal linkage, including: An alarm information receiving module is used to receive alarm information sent by an alarm system. The alarm information includes at least event location information and case description information. The candidate terminal filtering module is used to filter candidate vehicle terminals from multiple vehicle terminals based on the event location information, and to obtain the status information of each candidate vehicle terminal. The scoring calculation module is used to perform police force matching scoring on each candidate vehicle terminal based on the alarm information and the status information of each candidate vehicle terminal, and to determine the target vehicle terminal based on the police force matching score. The dispatch instruction module is used to receive and present dispatch instructions using the target vehicle terminal, obtain alarm feedback operations, and generate police officer operation results. The terminal feedback processing module is used to confirm that the police officer's operation result is that the police officer has accepted the task, continuously report location information using the target vehicle terminal, confirm that the target vehicle terminal has arrived at the event location, and collect on-site video data using the target vehicle terminal; The dynamic scheduling module is used to dynamically schedule officers based on their operational results, location information, and on-site video data, and to dispatch additional officers, replace dispatched officers, or coordinate dispatch of officers.

[0047] In some embodiments, the above-mentioned intelligent police dispatch system based on vehicle terminal linkage can also be implemented in the following ways.

[0048] like Figure 2 The diagram shows the structure of a public security intelligent dispatching system based on vehicle-mounted terminal linkage. In this embodiment, the public security intelligent dispatching system based on vehicle-mounted terminal linkage includes: An alarm information receiving module is used to receive alarm information sent by an alarm system. The alarm information includes at least event location information and case description information. The candidate terminal filtering module is used to filter candidate vehicle terminals from multiple vehicle terminals based on the event location information, and to obtain the status information of each candidate vehicle terminal. The scoring calculation module is used to score each candidate vehicle terminal based on the alarm information and the status information of each candidate vehicle terminal, and to determine the target vehicle terminal based on the scoring results. The dispatch command issuing module is used to send dispatch commands to the target vehicle terminal; The terminal feedback processing module is used to receive the police officer's operation results, location information and on-site video data fed back by the target vehicle terminal; The dynamic scheduling module is used to dynamically schedule based on the police officer's operation results, location information and on-site video data, and re-execute candidate vehicle terminal screening and police force matching scoring when the preset scheduling conditions are met, so as to increase, replace or coordinate police dispatch.

[0049] In some embodiments, the above-described intelligent police dispatching method based on vehicle terminal linkage can also be implemented in the following ways.

[0050] like Figure 3 The diagram shows a flowchart of a police intelligent dispatching method based on vehicle-mounted terminal linkage. In this embodiment, the core of the police intelligent dispatching method based on vehicle-mounted terminal linkage lies in the following: during the police dispatching process, the linkage between the vehicle-mounted terminal and the dispatching system organically combines candidate terminal screening, police force matching and scoring, police officer feedback, location tracking, on-site video transmission and dynamic rescheduling, thereby realizing a closed-loop intelligent dispatching method applicable to complex police scenarios.

[0051] In some embodiments of this invention, to improve the accuracy, real-time performance, and dynamic adaptability of dispatch decisions in complex emergency scenarios, this invention proposes a hierarchical adaptive dispatch decision-making algorithm based on multi-source risk perception and closed-loop feedback. This algorithm divides the dispatch process into a candidate terminal pre-screening stage, a target terminal matching and scoring stage, and a dynamic scheduling triggering stage, and constructs candidate screening values, police force matching scores, and dynamic scheduling triggering values ​​respectively, to achieve closed-loop decision control of vehicle-mounted terminals from pre-selection and optimization to re-scheduling.

[0052] The candidate terminal pre-screening stage is used to quickly eliminate vehicle-mounted terminals that are not suitable for participating in the current police situation; the target terminal matching and scoring stage is used to determine the optimal target vehicle-mounted terminal from the candidate terminals; and the dynamic scheduling triggering stage is used to determine whether it is necessary to redeploy police or increase the number of cooperating police forces based on feedback information and changes in the on-site situation during the task execution process.

[0053] Preferably, in order to eliminate the influence of the difference in the dimensions of different evaluation indicators on the comprehensive results, each factor involved in the calculation in this invention can be normalized so that its value falls within a preset range, such as the range of 0 to 1.

[0054] S1: Alarm Information Reception The system receives alarm information sent by the 110 alarm system. The alarm information includes at least the location of the event, case description information, alarm time, alarm type, and information about the person who made the alarm.

[0055] The event location can be the location actively reported by the alarm user, the location of the mobile terminal, or the geographic coordinates obtained by the alarm receiving system. The dispatch system performs structured parsing on the received alarm information, extracts basic fields related to dispatch decisions, and uses them as input data for subsequent candidate terminal screening and police force matching scoring.

[0056] S2: Candidate Terminal Screening Based on the location of the event, candidate vehicle terminals are selected from multiple vehicle terminals.

[0057] In this embodiment, the candidate terminal screening is not based solely on the spatial distance between the vehicle terminal and the event location, but rather on the pre-alarm accessibility constraint theory, comprehensively considering whether the vehicle terminal can "arrive, arrive quickly, and arrive stably," thereby constructing a multi-factor candidate pre-screening mechanism.

[0058] The aforementioned accessibility constraint theory for pre-dispatch of police incidents posits that, during the candidate terminal pre-screening stage, the primary factor influencing the effectiveness of dispatching police is not a single spatial distance, but rather comprehensive accessibility. This includes the time required for the terminal to reach the incident scene from its current location, the geographical accessibility of the route taken, weather-related disturbances, and the terminal's own stable operational capabilities. Based on this, this implementation introduces distance factors, estimated arrival time factors, geographical accessibility factors, weather impact factors, and terminal availability factors to generate candidate screening values.

[0059] Furthermore, a candidate screening value F can be constructed, and its calculation formula is as follows: F = a1·D + a2·T + a3·G + a4·W + a5·Q Where F is the candidate screening value; D is the distance factor; T is the estimated arrival time factor; G is the geographical accessibility factor; W is the weather impact factor; Q is the terminal availability factor; and a1 to a5 are the corresponding weight coefficients.

[0060] 1. Distance factor D The distance factor D is used to characterize the spatial proximity between the current location of the vehicle terminal and the event location. The distance can be a straight-line distance, a road network distance, or a passable distance based on the navigation path.

[0061] In one embodiment, normalization can be performed as follows: D = 1 - di / dmax, where di is the actual distance between the i-th vehicle terminal and the event location, and dmax is the preset maximum filtering distance. The closer the distance, the larger the distance factor D; the farther the distance, the smaller the distance factor D.

[0062] 2. Expected arrival time factor T The estimated arrival time factor T is used to characterize the efficiency of the time required for the vehicle-mounted terminal to reach the scene of the emergency. The estimated arrival time can be estimated by comprehensively considering real-time traffic conditions, road grade, historical average traffic speed, and weather conditions.

[0063] In one embodiment, the estimated arrival time factor T can be expressed as: T = 1 - ti / tmax, where ti is the estimated arrival time of the i-th vehicle terminal, and tmax is the preset maximum acceptable arrival time. The shorter the estimated arrival time, the larger T is.

[0064] 3. Geographical accessibility factor G The geographic accessibility factor G is used to characterize the road accessibility and route traversal difficulty between the current location of the vehicle terminal and the event location. The geographic accessibility can be determined based on one or more of the following: road connectivity, the presence of bridges or tunnels, mountainous or narrow road sections, closed areas, the number of feasible routes, and the degree of route detour.

[0065] In one embodiment, a hierarchical assignment method can be adopted: when the road is unobstructed and there are many alternative routes, G=1.0; when there is some detour or local restriction, G=0.6; when the road accessibility is poor or there is obvious blockage, G=0.2.

[0066] In another embodiment, the following method can also be used to calculate: G = np / nmax × (1-ri), where np is the number of feasible paths, nmax is the preset maximum number of paths, and ri is the detour coefficient of the i-th terminal path.

[0067] 4. Weather Influence Factor W The weather impact factor W is used to characterize the degree to which weather conditions affect police response efficiency. Weather information can be obtained from meteorological service platforms or regional police data platforms.

[0068] In one embodiment, a weather level mapping method can be used to determine W: W=1.0 for sunny or cloudy days; W=0.8 for light rain or light fog; W=0.5 for moderate rain or heavy fog; and W=0.2 for severe weather such as heavy rain or snow.

[0069] In another embodiment, the inverse function of the weather risk level can also be used: W = 1 - wr, where wr is the weather risk level value.

[0070] 5. Terminal available state factor Q The available state factor Q of the terminal is used to characterize whether the vehicle terminal currently has the ability to perform police dispatch tasks.

[0071] The availability status of the terminal can be determined based on at least the following factors: online status, current task status, network communication status, remaining battery power, video acquisition module status, and positioning module status.

[0072] In one embodiment, the terminal availability state factor Q can be expressed as: Q = q1·q2·q3·q4·q5, where q1 is the online status parameter, which is 1 when online and 0 when offline; q2 is the task status parameter, which is 1 when idle and 0 to 0.5 when busy; q3 is the network quality score; q4 is the battery adequacy score; and q5 is the video module availability score. The advantage of using a product-based structure is that when a certain key capability is severely deficient, the overall terminal availability state score can be significantly reduced, thereby avoiding the inclusion of terminals lacking stable execution capabilities in the candidate set.

[0073] 6. Explanation of weighting coefficients a1 to a5 In this implementation, the weighting coefficients for the candidate screening stage are determined based on the pre-alarm reachability constraint theory. This theory emphasizes that in the pre-screening stage, priority should be given to ensuring that the terminal has a high degree of certainty of arrival. Therefore, the weights of the expected arrival time and the terminal availability status can be higher than those of the weather disturbance factor.

[0074] Preferably, the weighting coefficients satisfy the following relationship: a2>a1, and a5>a4.

[0075] In one example, the possible values ​​are: a1=0.20, a2=0.30, a3=0.20, a4=0.10, a5=0.20.

[0076] In one embodiment, a candidate threshold F0 can be preset. When the candidate screening value F of a certain vehicle terminal is higher than or meets the preset threshold condition, the vehicle terminal is included in the candidate terminal set.

[0077] Preferably, the dispatching system can first perform a preliminary screening based on a preset geographical range, and then perform a secondary screening based on the candidate screening value F, so as to reduce computational complexity and improve the real-time performance of the screening.

[0078] S3: Terminal Status Acquisition Obtain the status information of each candidate vehicle-mounted terminal. The status information includes at least location information, online status, current task status, communication quality status, device operating status, and terminal-associated police officer information.

[0079] The communication quality status may include network latency, signal strength, and data upload stability; the device operating status may include the status of the video acquisition module, the status of the positioning module, and the terminal's battery level or power supply status; the terminal-associated police officer information may include the officer's ID number, police branch, historical dispatch records, and historical handling efficiency data. The dispatch system associates the status information with the alarm information for subsequent police force matching and scoring.

[0080] S4: Police Dispatch Score Calculation Based on alarm information and candidate vehicle terminal status information, the candidate vehicle terminals are scored for police force matching, and the target vehicle terminal is determined.

[0081] In this embodiment, the scoring process is constructed based on the police situation handling capability matching theory. The police situation handling capability matching theory holds that in the target terminal selection stage, it is necessary to consider not only whether the terminal can arrive at the scene quickly, but also whether the police officer corresponding to the terminal has the ability to handle the current police situation, and whether the terminal has stable reporting and video transmission capabilities, so as to ensure that the target terminal is "fast to arrive", "good at handling", and "stable in transmission".

[0082] Furthermore, a police force matching score S can be constructed, and its calculation formula is as follows: S = b1·R + b2·E + b3·U + b4·M + b5·C Where S is the police force matching score; R is the expected response efficiency factor; E is the police officer's historical handling efficiency factor; U is the current task load factor; M is the incident type matching factor; C is the communication and video capability factor; b1 to b5 are the corresponding weight coefficients.

[0083] 1. Expected response efficiency factor R The expected response efficiency factor R is used to characterize the efficiency of the target terminal from receiving the alarm to forming an effective on-site response. Its value can be determined by comprehensively considering the expected arrival time, current road traffic efficiency, historical average response performance in the same area, and current vehicle drivable speed.

[0084] In one embodiment, it can be expressed as: R = λ1(1-ti / tmax) + λ2vi + λ3hi, where ti is the expected arrival time, vi is the current drivability efficiency score, hi is the historical response performance score in the same area, and λ1+λ2+λ3=1.

[0085] 2. Historical disposal efficiency factor E The historical handling efficiency factor E is used to characterize the overall performance of terminal-associated police officers in handling historical police incidents. The historical handling efficiency can be determined based on one or more of the following: average call response time, average handling completion time, historical task success rate, and evaluation of the handling effect of similar cases.

[0086] In one embodiment, it can be expressed as: E = μ1er + μ2ec + μ3es, where er is the historical response efficiency score, ec is the historical processing completion efficiency score, es is the historical task success rate score, and μ1+μ2+μ3=1.

[0087] 3. Current task load factor U The current task load factor U is used to characterize the current busy / idle status of the target terminal and its remaining schedulable capacity. The current task load can be determined based on one or more of the following: the number of tasks currently being executed, the urgency of unfinished tasks, the number of consecutive emergency responses within the most recent preset time window, and the current duty status.

[0088] In one embodiment, a reverse scoring method is used: U = 1 - ui / umax, where ui is the current load value and umax is the preset maximum load value. The lower the terminal load, the higher U.

[0089] 4. Incident type matching factor M The incident type matching factor M is used to characterize the degree of business compatibility between the terminal-associated police officer and the current incident. The degree of compatibility can be determined based on one or more of the following: police type matching degree, historical experience in handling similar cases, equipment compatibility, and handling qualification level.

[0090] In one embodiment, a tiered assignment can be used: M=1.0 for a high match; M=0.7 for a medium match; and M=0.3 for a low match.

[0091] In another embodiment, it can be expressed as follows: M = ν1mp + ν2me + ν3mq, where mp is the police type matching degree, me is the experience degree of similar cases, mq is the equipment or qualification matching degree, and ν1+ν2+ν3=1.

[0092] 5. Communication and Video Capability Factor C The communication and video capability factor C is used to characterize the stability of the vehicle-mounted terminal in performing on-site information reporting and video transmission tasks. Its value can be determined based on one or more of the following: network uplink bandwidth, video acquisition resolution, video module stability, positioning module stability, and command reception success rate.

[0093] In one embodiment, it can be expressed as: C = ρ1cn + ρ2cv + ρ3cl, where cn is the network quality score, cv is the video module score, cl is the positioning and link stability score, and ρ1+ρ2+ρ3=1.

[0094] 6. Explanation of weighting coefficients b1 to b5 In this implementation, the weighting coefficients for the scoring phase are determined based on the emergency response capability matching theory. This theory emphasizes that, in the target optimization phase, expected response efficiency and emergency response matching degree are core factors, historical response efficiency serves as a capability correction factor, and current task load and communication video capabilities serve as execution guarantee factors.

[0095] Preferably, the weighting coefficients satisfy the following relationship: b1≈b4>b2>b3, b5.

[0096] In one example, the possible values ​​are: b1=0.28, b2=0.20, b3=0.15, b4=0.25, b5=0.12.

[0097] In one embodiment, the police dispatch system sorts the police force matching scores S of the candidate vehicle terminals and selects the vehicle terminal with the highest score as the target vehicle terminal.

[0098] Weight adaptive adjustment mechanism In some embodiments of the present invention, in order to improve the adaptability to different police scenarios, a police scenario-driven weight adaptive adjustment algorithm may be introduced.

[0099] The core idea of ​​the algorithm is that different types of alarms have different requirements for response speed, on-site video capabilities, handling experience and risk identification capabilities. Therefore, the weight coefficients in the candidate screening formula, scoring formula and dynamic scheduling formula are not fixed, but can be dynamically adjusted according to the type of alarm.

[0100] It can be expressed as: Wk′ = Wk + Δk(type), where Wk is the original weight, Wk′ is the weight after the alarm type is corrected, and Δk(type) is the weight correction term based on the alarm type.

[0101] For example, in traffic accident-related police incidents, the weights of the estimated arrival time factor, the estimated response efficiency factor, and the communication and video capability factor can be increased; in public security dispute-related police incidents, the weights of the historical handling efficiency factor and the incident type matching factor can be increased; and in mass incident-related police incidents, the weights of the video risk identification factor and the historical incident correlation factor can be increased.

[0102] S5: Police dispatch order issued A dispatch command is sent to the target vehicle-mounted terminal. The dispatch command includes at least the event information, event location, incident type, response level, and task number. Preferably, the dispatch command may also include a recommended driving route, on-site precautions, and suggestions for coordinated handling. Upon receiving the dispatch command, the vehicle-mounted terminal parses the command content and enters a state awaiting officer confirmation.

[0103] S6: Police Officer Interaction Feedback The vehicle-mounted terminal will present the dispatch order to the police officer and receive the officer's feedback. The feedback includes at least confirming the dispatch, rejecting the dispatch, requesting assistance, and reporting the current abnormal status.

[0104] In one embodiment, the vehicle-mounted terminal presents the task content to the police officer through a graphical interface, voice broadcast, or pop-up prompts, and records the officer's operation time and operation results.

[0105] S7: Feedback Processing The vehicle-mounted terminal feeds back the results of the police officers' actions to the dispatch system.

[0106] When an officer accepts a mission, the dispatch system updates the target vehicle terminal status to "in progress" and enters the mission tracking phase. If the officer refuses the mission or fails to respond within a preset time, the dispatch system determines that the dispatch has failed and re-executes the candidate terminal screening and police force matching scoring process to select a new target vehicle terminal.

[0107] Preferably, the dispatch system can also record the reasons for rejection, reasons for no response, and the number of times the task was returned, as a data basis for subsequent dispatch strategy optimization.

[0108] S8: Police Dispatch Process Tracking During the police officers' response to the call, the vehicle-mounted terminal continuously reported location information, driving status information, and mission execution status information.

[0109] The location information may include real-time coordinates, movement speed, movement direction, and current location timestamp; the task execution status information may include status indicators such as departed, en route, about to arrive, arrived, and handling. The dispatch system tracks the movement trajectory of the target vehicle terminal based on continuously reported location information and, in conjunction with a preset route, determines whether there are any instances of delayed arrival, route deviation, or abnormal stoppage.

[0110] S9: On-site video capture and transmission Once the vehicle-mounted terminal arrives at the scene, it activates the video acquisition module to collect on-site video data and transmits it back to the dispatch system via the communication network.

[0111] Preferably, the video acquisition process includes: starting the video acquisition device, acquiring the video stream in segments, extracting keyframe images, and synchronously uploading the video stream and keyframe data to the dispatch system. In one embodiment, the dispatch system can perform structured analysis on the returned video data to obtain information on the density of the crowd, vehicle congestion, abnormal behavior characteristics, and risk level, for subsequent dynamic dispatching.

[0112] S10: Dynamic Scheduling The police dispatch system dynamically schedules officers based on feedback information and video data.

[0113] In this embodiment, the dynamic scheduling is constructed based on the theory of on-site risk mutation triggering. The theory of on-site risk mutation triggering states that a single location anomaly, a single manual feedback, or a single video event may lead to false triggering or missed triggering. Dynamic scheduling should comprehensively consider execution anomalies, changes in on-site risks, police feedback, and historical regional risk background to make a comprehensive judgment on whether to initiate rescheduling.

[0114] S10.1: Abnormal State Identification It receives location information, status information, and on-site video data continuously reported by the vehicle terminal to determine whether there is any abnormal status in the current task.

[0115] The abnormal states include at least: failure to arrive at the scene for an extended period of time; deviation from the preset route; prolonged stagnation; officers actively requesting support; increased risk level shown in on-site video; mission failure or escalation of the emergency.

[0116] S10.2: Video Risk Analysis Keyframes are extracted from the returned video data, and the on-site situation is analyzed in conjunction with preset risk identification rules.

[0117] The risk identification rules can be used to identify: crowd gatherings; conflict escalation; traffic congestion; dangerous behavior; rapid gathering or spread of suspicious targets; and other preset high-risk events.

[0118] S10.3: Dynamic Scheduling Decision Based on location feedback anomalies, video risk analysis results, police officer feedback anomalies, and historical incident correlation information, the dynamic dispatch trigger value P is calculated using the following formula: P = c1·L + c2·V + c3·A + c4·H Wherein, P is the dynamic scheduling trigger value; L is the location anomaly factor; V is the video risk identification factor; A is the police officer feedback anomaly factor; H is the historical police incident correlation factor; and c1 to c4 are the corresponding weight coefficients.

[0119] 1. Location anomaly degree factor L The location anomaly factor L is used to characterize the degree of anomaly that occurs when the target vehicle terminal is in motion. Its value can be determined by combining one or more of the following factors: degree of failure to arrive on time, degree of route deviation, degree of prolonged stagnation, and degree of abnormal detour.

[0120] In one embodiment, it can be expressed as: L = η1lt + η2ld + η3ls, where lt is the timeout level, ld is the yaw level, ls is the stall level, and η1+η2+η3=1.

[0121] 2. Video Risk Identification Factor V The video risk identification factor V is used to characterize the risk level identified from the on-site video. Its value can be determined based on one or more of the identification results of personnel density, intensity of abnormal behavior, degree of traffic congestion, and environmental hazard characteristics.

[0122] In one embodiment, it can be expressed as: V = θ1vc + θ2vb + θ3vr, where vc is the cluster risk score, vb is the behavioral abnormality score, vr is the environmental hazard score, and θ1+θ2+θ3=1.

[0123] 3. Police officer reports abnormal factor A The police officer feedback anomaly factor A is used to characterize the degree of anomaly in the proactive feedback from police officers. The anomaly feedback may include: requesting backup; reporting loss of control at the scene; reporting an increase in the number of suspects; reporting obstruction of execution; and reporting equipment malfunction.

[0124] In one embodiment, a tiered assignment method can be adopted: A=0 when there is no abnormality; A=0.4 when there is a general abnormality; A=0.7 when there is a significant abnormality; and A=1.0 when there is an emergency abnormality.

[0125] 4. Historical Police Incident Correlation Factor H The historical incident correlation factor H is used to characterize the current region's risk background in a historical dimension. Its value can be determined based on one or more of the following: the historical frequency of similar incidents in the region, the proportion of historical incidents that escalated into mass incidents, the region's sensitivity level, and risk weighting for specific time periods.

[0126] In one embodiment, it can be expressed as: H = σ1hf + σ2hu + σ3hs, where hf is the historical frequency, hu is the historical escalation level, hs is the regional sensitivity, and σ1+σ2+σ3=1.

[0127] 5. Explanation of weighting coefficients c1 to c4 In this implementation, the weighting coefficients for the dynamic scheduling phase are determined based on the theory of sudden on-site risk triggering. This theory emphasizes that video risk identification results most directly reflect changes on-site, location anomalies and police officer feedback are used to reflect task execution deviations and frontline perception, and historical incident correlation information serves as a background correction factor.

[0128] Preferably, the weighting coefficients satisfy the following relationships: c2>c1, c3≈c1, and c4 <c2。

[0129] In one example, we can take the following values: c1=0.25, c2=0.35, c3=0.25, c4=0.15.

[0130] When the dynamic scheduling trigger value P is higher than the preset threshold P0, the dynamic scheduling process is started.

[0131] S10.4: Reschedule execution In the dynamic dispatch process, the police dispatch system re-acquires the status information of the vehicle-mounted terminals around the current police situation, and re-executes steps S2 and S4 on the updated candidate terminal set to redetermine the target vehicle-mounted terminal.

[0132] Based on the recalculation results, the dispatch system can perform one or more of the following dispatch actions: dispatch additional nearby police officers; replace the current executing terminal; instruct multiple terminals to coordinate the handling; escalate the incident to the superior command center; and adjust the task priority and handling strategy.

[0133] The above methods enable closed-loop dynamic control in complex police scenarios, from candidate selection and target optimization to risk-triggered rescheduling.

[0134] S11: Mission Complete After completing the on-site handling, the police officers reported the results through the vehicle-mounted terminal.

[0135] The processing results shall include at least: task completion status; arrival time; processing end time; processing result description; on-site photos or video summary; and whether further follow-up is required.

[0136] After receiving the processing result, the dispatch system updates the status of the task to "completed" and stores the screening data, scoring data, trajectory data, video data and dispatch results during the task execution process as historical task records for subsequent model optimization, dispatch strategy iteration and case review analysis.

[0137] Example application: In traffic accident handling scenarios, after receiving traffic accident alarm information, the 110 alarm system first analyzes the accident location and alarm type, and obtains the location, online status and task status information of multiple vehicle terminals around the accident.

[0138] The dispatch system first pre-screens nearby vehicle terminals based on candidate screening values, eliminating terminals with excessively long expected arrival times, poor geographical accessibility, or unusable status. Then, it optimizes the candidate terminals based on police force matching scores, identifying target vehicle terminals with high response efficiency, strong historical handling capabilities, and stable video transmission capabilities.

[0139] After receiving a dispatch order, the target vehicle-mounted terminal confirms receipt of the order and proceeds to the scene. During the dispatch, the vehicle-mounted terminal continuously reports its location information. Upon arrival at the scene, the vehicle-mounted terminal activates its video capture module and transmits the video footage back to the dispatch system. The dispatch system identifies risk characteristics such as increased traffic congestion and crowd gathering based on video analysis results. When the dynamic dispatch trigger value calculated by the system, combining the degree of location anomaly, the degree of anomaly reported by the officer, and the correlation with historical incidents, exceeds a preset threshold, the system automatically initiates a dynamic dispatch process, re-selects nearby police forces, and dispatches additional coordinating terminals to handle the situation, thereby improving response efficiency and accuracy in complex traffic accident scenarios. Figure 4 The diagram shows the timing sequence of intelligent police dispatch based on vehicle-mounted terminal linkage.

[0140] Example 2 In one specific embodiment, taking a traffic accident alarm as an example, after the alarm system receives an alarm message that two vehicles collided on a certain road section, the dispatch system obtains the real-time status information of eight vehicle-mounted terminals around the accident site, and pre-screens the eight vehicle-mounted terminals based on candidate screening values.

[0141] In this embodiment, the formula for the candidate screening value is: F = a1·D + a2·T + a3·G + a4·W + a5·Q The weighting coefficients are set as follows: a1=0.20, a2=0.30, a3=0.20, a4=0.10, a5=0.20, and the candidate screening threshold is set as F0=0.60. The distance factor D is normalized based on the road distance between the terminal and the accident location; the estimated arrival time factor T is normalized based on the estimated arrival time from real-time navigation; the geographical accessibility factor G is assigned a graded value based on whether there are road closures, detours, or bridge / tunnel restrictions; the weather impact factor W is assigned a value based on the weather conditions at the time of the accident; and the terminal availability status factor Q is determined comprehensively based on the terminal's online status, task status, network quality, and video module status.

[0142] Calculations showed that 5 out of the 8 vehicle-mounted terminals had candidate screening values ​​higher than the threshold F0, and thus entered the candidate terminal set. Table 1 shows the candidate screening parameters and results for 6 representative vehicle-mounted terminals.

[0143] Table 1: Candidate screening parameters and results for vehicle-mounted terminals.

[0144]

[0145] As shown in Table 1, terminal A3 has the highest candidate screening value. Terminals A4 and A6 were not included in the candidate terminal set due to their long expected arrival time, poor geographical accessibility, or low overall terminal availability.

[0146] Subsequently, the dispatching system calculates a police force matching score based on the candidate terminal set: S = b1·R + b2·E + b3·U + b4·M + b5·C The weighting coefficients were set as follows: b1=0.28, b2=0.20, b3=0.15, b4=0.25, and b5=0.12. Calculations showed that among the five candidate terminals, the vehicle terminal numbered A3 had the highest score and was therefore selected as the target vehicle terminal.

[0147] During mission execution, if the video data transmitted back by the vehicle terminal shows that people are gathering at the accident scene and road congestion is rapidly worsening, and the location information shows that the target vehicle terminal experiences a brief pause, then the dispatch system calculates the dynamic dispatch trigger value: P = c1·L + c2·V + c3·A + c4·H The weighting coefficients are set as follows: c1=0.25, c2=0.35, c3=0.25, c4=0.15, and the dynamic dispatch threshold is set as P0=0.65. When P>P0 is calculated, the dispatch system automatically triggers the dynamic dispatch process and re-selects and dispatches one additional collaborative vehicle terminal from the vicinity of the accident site to participate in the handling, thereby improving the efficiency of traffic control and handling at the accident scene.

[0148] Example 3 To verify the technical effectiveness of the present invention, traffic accidents, public security disputes, and road congestion were selected as test samples. In an exemplary comparative verification scenario, the present invention was compared with the traditional method of dispatching police solely based on distance. Figure 5 The image shown is a comparison and verification result chart.

[0149] Traditional police dispatch methods select target terminals based solely on their distance from the location of the incident, without considering factors such as estimated arrival time, terminal status, incident type matching, video risk identification, and dynamic dispatch triggering mechanisms. The present invention employs a multi-factor candidate screening, police force matching scoring, and a dynamic dispatch mechanism jointly driven by location, video, and feedback.

[0150] The comparison metrics include: average arrival time, target terminal selection accuracy, rescheduling success rate under abnormal alarms, and whether closed-loop processing is supported. Table 2 provides exemplary comparison and verification results.

[0151] Table 2: Comparison and Verification Results

[0152] As shown in Table 2, compared with the traditional single-distance dispatch method, the present invention has significant advantages in terms of average arrival time, target terminal selection accuracy, and rescheduling success rate under abnormal alarm conditions. At the same time, it can realize closed-loop processing of dispatch, execution, feedback and rescheduling.

[0153] Furthermore, in the present invention, by comprehensively considering the expected arrival time, geographical environment, weather environment, and terminal status during the candidate terminal screening stage, the probability of unsuitable terminals entering the candidate set can be effectively reduced. During the target terminal selection stage, by introducing a police force matching scoring mechanism, the compatibility between the target terminal and the current emergency situation can be improved. During the task execution stage, dynamic scheduling is jointly driven by location feedback, on-site video, and abnormal police officer feedback, enabling timely triggering of additional or replacement dispatches when on-site risks increase. Therefore, the present invention effectively improves the problems of reliance on experience, single screening dimensions, scheduling lag, and lack of closed-loop optimization in traditional dispatch methods.

[0154] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the above-described intelligent police dispatch method based on vehicle terminal linkage.

[0155] like Figure 6As shown, the electronic device 120 may include: at least one processor 121, such as a central processing unit (CPU), at least one communication interface 123, a memory 124, and at least one communication bus 122. The communication bus 122 is used to enable communication between these components. The communication interface 123 may include a display screen or a keyboard; optionally, the communication interface 123 may also include a standard wired interface or a wireless interface. The memory 124 may be high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory 124 may also be at least one storage device located remotely from the aforementioned processor 121. The memory 124 stores application programs, and the processor 121 calls the program code stored in the memory 124 to execute any of the aforementioned method steps. The communication bus 122 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication bus 122 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6The term 124 is represented by a single line, but this does not imply a single bus or a single type of bus. The memory 124 may include volatile memory, such as random-access memory (RAM); it may also include non-volatile memory, such as flash memory, hard disk drive (HDD), or solid-state drive (SSD); or it may include combinations of the above types of memory. The processor 121 may be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and an NP. The processor 121 may further include hardware chips. These hardware chips may be application-specific integrated circuits (ASICs), programmable logic devices (PLDs), or combinations thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof. Optionally, the memory 124 is also used to store program instructions. The processor 121 can call the program instructions to implement the intelligent police dispatch method based on vehicle terminal linkage as described in this embodiment.

[0156] This embodiment provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described intelligent police dispatch method based on vehicle terminal linkage.

[0157] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for intelligent police dispatching based on vehicle-mounted terminal linkage, characterized in that, Includes the following steps: S1: Receive alarm information sent by the alarm system, wherein the alarm information includes at least event location information and case description information; S2: Based on the event location information, select candidate vehicle terminals from multiple vehicle terminals and obtain the status information of each candidate vehicle terminal; S3: Based on the alarm information and the status information of each candidate vehicle terminal, a police force matching score is performed on each candidate vehicle terminal, and the target vehicle terminal is determined based on the police force matching score. S4: Utilize the target vehicle terminal to receive and present the dispatch command, obtain the alarm feedback operation, and generate the police officer's operation result; S5: Confirm that the police officer's operation result is that the police officer accepts the task, continuously report the location information using the target vehicle terminal, confirm that the target vehicle terminal has arrived at the event location, and collect on-site video data using the target vehicle terminal; S6: Dynamic scheduling is performed based on the police officer's operation results, location information, and on-site video data to dispatch additional, replace, or coordinate dispatch of police officers.

2. The intelligent police dispatching method based on vehicle-mounted terminal linkage according to claim 1, characterized in that, The step of selecting candidate vehicle terminals from multiple vehicle terminals based on the event location information includes: obtaining the spatial distance between each vehicle terminal and the event location, estimated arrival time, geographical environment information, weather environment information, social environment information, and the current status information of the vehicle terminal; calculating the candidate screening value corresponding to each vehicle terminal based on the spatial distance, estimated arrival time, geographical environment information, weather environment information, social environment information, and the current status information of the vehicle terminal; and determining the vehicle terminals whose candidate screening values ​​meet the preset screening conditions as candidate vehicle terminals.

3. The intelligent police dispatching method based on vehicle-mounted terminal linkage according to claim 2, characterized in that, The formula for calculating the candidate screening value is: F = a1·D + a2·T + a3·G + a4·W + a5·Q Where F is the candidate screening value, D is the distance factor, T is the estimated arrival time factor, G is the geographical accessibility factor, W is the weather impact factor, Q is the terminal availability factor, and a1, a2, a3, a4 and a5 are the corresponding weight coefficients.

4. The intelligent police dispatching method based on vehicle-mounted terminal linkage according to claim 1, characterized in that, Step S3 specifically includes: calculating the police force matching score of each candidate vehicle terminal based on the status information of each candidate vehicle terminal; sorting the candidate vehicle terminals according to their police force matching scores, and selecting the candidate vehicle terminal with the highest police force matching score as the target vehicle terminal.

5. The intelligent police dispatching method based on vehicle-mounted terminal linkage according to claim 4, characterized in that, The formula for calculating the police force matching score is as follows: S = b1·R + b2·E + b3·U + b4·M + b5·C Where S is the police force matching score, R is the expected response efficiency factor, E is the police officer's historical handling efficiency factor, U is the current task load factor, M is the incident type matching factor, C is the communication and video capability factor, and b1, b2, b3, b4 and b5 are the corresponding weight coefficients.

6. The intelligent police dispatching method based on vehicle-mounted terminal linkage according to claim 1, characterized in that, The dynamic scheduling process includes: The location information continuously reported by the target vehicle terminal is analyzed to obtain a location analysis result. The location analysis result includes location anomalies, which include failure to arrive within time limit, deviation from the preset route, and long-term stagnation. Keyframe extraction and risk identification are performed on the on-site video data to obtain video risk identification results, which include crowd gathering, conflict escalation, traffic congestion, and pre-set dangerous behaviors. Based on the location anomaly, video risk identification results, police officer feedback on the degree of anomaly, and historical police incident correlation information, a dynamic dispatch trigger value is calculated; when the dynamic dispatch trigger value is higher than a preset threshold, steps S2 and S3 are executed.

7. The intelligent police dispatching method based on vehicle-mounted terminal linkage according to claim 6, characterized in that, The formula for calculating the dynamic scheduling trigger value is: P = c1·L + c2·V + c3·A + c4·H Where P is the dynamic scheduling trigger value, L is the location anomaly factor, V is the video risk identification factor, A is the police officer feedback anomaly factor, H is the historical police incident correlation factor, and c1, c2, c3 and c4 are the corresponding weight coefficients.

8. A public security intelligent dispatch system based on vehicle-mounted terminal linkage, characterized in that, include: An alarm information receiving module is used to receive alarm information sent by an alarm system. The alarm information includes at least event location information and case description information. The candidate terminal filtering module is used to filter candidate vehicle terminals from multiple vehicle terminals based on the event location information, and to obtain the status information of each candidate vehicle terminal. The scoring calculation module is used to perform police force matching scoring on each candidate vehicle terminal based on the alarm information and the status information of each candidate vehicle terminal, and to determine the target vehicle terminal based on the police force matching score. The dispatch instruction module is used to receive and present dispatch instructions using the target vehicle terminal, obtain alarm feedback operations, and generate police officer operation results. The terminal feedback processing module is used to confirm that the police officer's operation result is that the police officer has accepted the task, continuously report location information using the target vehicle terminal, confirm that the target vehicle terminal has arrived at the event location, and collect on-site video data using the target vehicle terminal; The dynamic scheduling module is used to dynamically schedule officers based on their operational results, location information, and on-site video data, and to dispatch additional officers, replace dispatched officers, or coordinate dispatch of officers.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent police dispatching method based on vehicle terminal linkage as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent police dispatch method based on vehicle terminal linkage as described in any one of claims 1-7.

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